General Information
This subject enables students to apply appropriate marketing analytical tools and techniques to address a range of marketing challenges. Importantly, it will also highlight the role and importance of marketing analytics to support a data-driven approach to marketing strategy and decision making. Through a variety of applied activities and assignments, students will have the opportunity to develop a thorough conceptual understanding of marketing analytics and its applications.
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Details
Academic unit: Bond Business School Subject code: MKTG71-315 Subject title: Marketing Analytics Subject level: Postgraduate Semester/Year: September 2023 Credit points: 10.000 -
Delivery & attendance
Timetable: https://bond.edu.au/timetable Delivery mode: Standard Workload items: - Computer Lab: x12 (Total hours: 24) - Computer Lab 1
- Computer Lab: x12 (Total hours: 24) - Computer Lab 2
- Personal Study Hours: x12 (Total hours: 72) - Recommended study time & reviewing materials
Attendance and learning activities: Attendance at all class sessions is expected. Students are expected to notify the instructor of any absences with as much advance notice as possible. -
Resources
Prescribed resources: Books
- Robert W. Palmatier,J. Andrew Petersen,Frank Germann (2022). Marketing Analytics. n/a, Bloomsbury Publishing 433
iLearn@Bond & Email: iLearn@Bond is the Learning Management System at Bond University and is used to provide access to subject materials, class recordings and detailed subject information regarding the subject curriculum, assessment, and timing. Both iLearn and the Student Email facility are used to provide important subject notifications.
Additionally, official correspondence from the University will be forwarded to students’ Bond email account and must be monitored by the student.
To access these services, log on to the Student Portal from the Bond University website as www.bond.edu.au
| Academic unit: | Bond Business School |
|---|---|
| Subject code: | MKTG71-315 |
| Subject title: | Marketing Analytics |
| Subject level: | Postgraduate |
| Semester/Year: | September 2023 |
| Credit points: | 10.000 |
| Timetable: | https://bond.edu.au/timetable |
|---|---|
| Delivery mode: | Standard |
| Workload items: |
|
| Attendance and learning activities: | Attendance at all class sessions is expected. Students are expected to notify the instructor of any absences with as much advance notice as possible. |
| Prescribed resources: | Books
|
|---|---|
| iLearn@Bond & Email: | iLearn@Bond is the Learning Management System at Bond University and is used to provide access to subject materials, class recordings and detailed subject information regarding the subject curriculum, assessment, and timing. Both iLearn and the Student Email facility are used to provide important subject notifications. Additionally, official correspondence from the University will be forwarded to students’ Bond email account and must be monitored by the student. To access these services, log on to the Student Portal from the Bond University website as www.bond.edu.au |
Enrolment requirements
| Requisites: |
Nil |
|---|---|
| Assumed knowledge: |
Assumed knowledge is the minimum level of knowledge of a subject area that students are assumed to have acquired through previous study. It is the responsibility of students to ensure they meet the assumed knowledge expectations of the subject. Students who do not possess this prior knowledge are strongly recommended against enrolling and do so at their own risk. No concessions will be made for students’ lack of prior knowledge. Assumed Prior Learning (or equivalent): |
| Restrictions: |
Nil |
Assurance of learning
Assurance of Learning means that universities take responsibility for creating, monitoring and updating curriculum, teaching and assessment so that students graduate with the knowledge, skills and attributes they need for employability and/or further study.
At Bond University, we carefully develop subject and program outcomes to ensure that student learning in each subject contributes to the whole student experience. Students are encouraged to carefully read and consider subject and program outcomes as combined elements.
Program Learning Outcomes (PLOs)
Program Learning Outcomes provide a broad and measurable set of standards that incorporate a range of knowledge and skills that will be achieved on completion of the program. If you are undertaking this subject as part of a degree program, you should refer to the relevant degree program outcomes and graduate attributes as they relate to this subject.
Subject Learning Outcomes (SLOs)
On successful completion of this subject the learner will be able to:
- Demonstrate advanced knowledge of marketing analytics and its role and importance in supporting marketing strategy.
- Apply appropriate analytical tools including cluster analysis, regression analysis, survey design and testing, conjoint analysis, and experiments to understand complex marketing problems and generate insights.
- Collaborate with others in a team project to select and use appropriate analytical tools to solve complex marketing problems.
- Communicate data-driven insights and formulate managerial recommendations in a professionally written, clear, and concise strategic marketing report suitable for submission to executive level marketing professionals.
Generative Artificial Intelligence in Assessment
The University acknowledges that Generative Artificial Intelligence (Gen-AI) tools are an important facet of contemporary life. Their use in assessment is considered in line with students’ development of the skills and knowledge which demonstrate learning outcomes and underpin study and career success. Instructions on the use of Gen-AI are given for each assessment task; it is your responsibility to adhere to these instructions.
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Assessment details
Type Task % Timing* Outcomes assessed Assignment Replication assignment 1 10.00% Week 3 1,2,4 Project Plan§ Team project – Project Plan 5.00% Week 4 2,3,4 Assignment Replication assignment 2 10.00% Week 6 1,2,4 Project Report§ Team project – Interim Project Report 10.00% Week 7 2,3,4 Assignment Replication assignment 3 10.00% Week 9 1,2,4 Assignment Replication assignment 4 10.00% Week 12 1,2,4 Project Report§ Team Project – Final Project Report 25.00% Week 13 2,3,4 Student Engagement Class participation and engagement 20.00% Ongoing 1,3 - § Indicates group/teamwork-based assessment
- * Assessment timing is indicative of the week that the assessment is due or begins (where conducted over multiple weeks), and is based on the standard University academic calendar
- C = Students must reach a level of competency to successfully complete this assessment.
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Assessment criteria
Assessment criteria
High Distinction 85-100 Outstanding or exemplary performance in the following areas: interpretative ability; intellectual initiative in response to questions; mastery of the skills required by the subject, general levels of knowledge and analytic ability or clear thinking. Distinction 75-84 Usually awarded to students whose performance goes well beyond the minimum requirements set for tasks required in assessment, and who perform well in most of the above areas. Credit 65-74 Usually awarded to students whose performance is considered to go beyond the minimum requirements for work set for assessment. Assessable work is typically characterised by a strong performance in some of the capacities listed above. Pass 50-64 Usually awarded to students whose performance meets the requirements set for work provided for assessment. Fail 0-49 Usually awarded to students whose performance is not considered to meet the minimum requirements set for particular tasks. The fail grade may be a result of insufficient preparation, of inattention to assignment guidelines or lack of academic ability. A frequent cause of failure is lack of attention to subject or assignment guidelines. Quality assurance
For the purposes of quality assurance, Bond University conducts an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.
| Type | Task | % | Timing* | Outcomes assessed |
|---|---|---|---|---|
| Assignment | Replication assignment 1 | 10.00% | Week 3 | 1,2,4 |
| Project Plan§ | Team project – Project Plan | 5.00% | Week 4 | 2,3,4 |
| Assignment | Replication assignment 2 | 10.00% | Week 6 | 1,2,4 |
| Project Report§ | Team project – Interim Project Report | 10.00% | Week 7 | 2,3,4 |
| Assignment | Replication assignment 3 | 10.00% | Week 9 | 1,2,4 |
| Assignment | Replication assignment 4 | 10.00% | Week 12 | 1,2,4 |
| Project Report§ | Team Project – Final Project Report | 25.00% | Week 13 | 2,3,4 |
| Student Engagement | Class participation and engagement | 20.00% | Ongoing | 1,3 |
- § Indicates group/teamwork-based assessment
- * Assessment timing is indicative of the week that the assessment is due or begins (where conducted over multiple weeks), and is based on the standard University academic calendar
- C = Students must reach a level of competency to successfully complete this assessment.
Assessment criteria
| High Distinction | 85-100 | Outstanding or exemplary performance in the following areas: interpretative ability; intellectual initiative in response to questions; mastery of the skills required by the subject, general levels of knowledge and analytic ability or clear thinking. |
|---|---|---|
| Distinction | 75-84 | Usually awarded to students whose performance goes well beyond the minimum requirements set for tasks required in assessment, and who perform well in most of the above areas. |
| Credit | 65-74 | Usually awarded to students whose performance is considered to go beyond the minimum requirements for work set for assessment. Assessable work is typically characterised by a strong performance in some of the capacities listed above. |
| Pass | 50-64 | Usually awarded to students whose performance meets the requirements set for work provided for assessment. |
| Fail | 0-49 | Usually awarded to students whose performance is not considered to meet the minimum requirements set for particular tasks. The fail grade may be a result of insufficient preparation, of inattention to assignment guidelines or lack of academic ability. A frequent cause of failure is lack of attention to subject or assignment guidelines. |
Quality assurance
For the purposes of quality assurance, Bond University conducts an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.
Study Information
Submission procedures
Students must check the iLearn@Bond subject site for detailed assessment information and submission procedures.
Policy on late submission and extensions
A late penalty will be applied to all overdue assessment tasks unless an extension is granted by the lead educator. The standard penalty will be 10% of marks awarded to that assessment per day late with no assessment to be accepted seven days after the due date. Where a student is granted an extension, the penalty of 10% per day late starts from the new due date.
Academic Integrity
Bond University‘s Student Code of Conduct Policy , Student Charter, Academic Integrity Policy and our Graduate Attributes guide expectations regarding student behaviour, their rights and responsibilities. Information on these topics can be found on our Academic Integrity webpage recognising that academic integrity involves demonstrating the principles of integrity (honesty, fairness, trust, professionalism, courage, responsibility, and respect) in words and actions across all aspects of academic endeavour.
Staff are required to report suspected misconduct. This includes all types of plagiarism, cheating, collusion, fabrication or falsification of data/content or other misconduct relating to assessment such as the falsification of medical certificates for assessment extensions. The longer term personal, social and financial consequences of misconduct can be severe, so please ask for help if you are unsure.
If your work is subject to an inquiry, you will be given an opportunity to respond and appropriate support will be provided. Academic work under inquiry will not be marked until the process has concluded. Penalties for misconduct include a warning, reduced grade, a requirement to repeat the assessment, suspension or expulsion from the University.
Feedback on assessment
Feedback on assessment will be provided to students according to the requirements of the Assessment Procedure Schedule A - Assessment Communication Procedure.
Whilst in most cases feedback should be provided within two weeks of the assessment submission due date, the Procedure should be checked if the assessment is linked to others or if the subject is a non-standard (e.g., intensive) subject.
Accessibility and Inclusion Support
Support is available to students where a physical, mental or neurological condition exists that would impact the student’s capacity to complete studies, exams or assessment tasks. For effective support, special requirement needs should be arranged with the University in advance of or at the start of each semester, or, for acute conditions, as soon as practicable after the condition arises. Reasonable adjustments are not guaranteed where applications are submitted late in the semester (for example, when lodged just prior to critical assessment and examination dates).
As outlined in the Accessibility and Inclusion Policy, to qualify for support, students must meet certain criteria. Students are also required to meet with the Accessibility and Inclusion Advisor who will ensure that reasonable adjustments are afforded to qualifying students.
For more information and to apply online, visit BondAbility.
Additional subject information
A peer-evaluation system will be used in this subject to help determine the individual marks for all group assessments. As part of the requirements for Business School quality accreditation, the Bond Business School employs an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.
Subject curriculum
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Introduction to marketing analytics
Introduces the concept of marketing analytics and when and why they are used in business. The value of marketing analytics is considered from a firm and individual perspective. The First Principles framework for marketing is introduced, as is the software R and Tableau.
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Principle 1: All Customers are Different
A fundamental issue for marketing managers is that all customers differ, and an effective marketing strategy must manage ever present customer heterogeneity. Sources of customer heterogeneity (e.g., individual differences, life experiences, functional needs, and self-identity/image) are reviewed and analytical tools for segmentation, targeting, and positioning are introduced. Cluster analysis for segmentation, discriminant analysis for targeting and classification, and perceptual mapping techniques for competitive positioning are explored conceptually and then applied technically through R and Tableau. Each techniques’ links to developing effective marketing strategy is summarised.
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Principle 2: All Customers Change
All marketing strategies must evolve over time in response to the changing needs and wants of customers. Responding to customer dynamics is vital to avoid obsolescence. Sources of customer dynamics, including individual level (e.g., discrete life events, product learning effects), product market level (e.g., product life cycles), and environmental level (e.g., changes in the economy, industry, or culture) events are reviewed. Tools to respond to these changes, including regression analysis and customer lifetime value, are covered conceptually and then applied technically through R and Tableau.
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Principle 3: All Competitors React
All markets include competitors who may imitate a firms’ successful strategies or create novel competing offerings to lure customers away from the firm. Marketing managers must therefore be able to build and maintain a sustainable competitive advantage (SCA) to protect the firm from competitor’s reactions. The tools and methods of survey design and testing to derive customer insights, and conjoint analysis for product and pricing decisions are introduced conceptually and then applied technically through R and Tableau.
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Principle 4: All Resources are Limited
All firms have limited resources and an effective marketing strategy must manage ongoing resource trade-offs in decision making. Developing marketing mixes to manage customer heterogeneity, changing customer needs, and competitor reactions require tools to efficiently allocate resources to optimise return on investment. Tools including Ordinary Least Squares regression to estimate sales, and experiments to establish cause-and-effect are introduced conceptually and then applied technically through R and Tableau. How these tools optimise marketing mixes is summarised.